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GECCO
2006
Springer
147views Optimization» more  GECCO 2006»
13 years 11 months ago
Deceptiveness and neutrality the ND family of fitness landscapes
When a considerable number of mutations have no effects on fitness values, the fitness landscape is said neutral. In order to study the interplay between neutrality, which exists ...
William Beaudoin, Sébastien Vérel, P...
GECCO
2010
Springer
191views Optimization» more  GECCO 2010»
13 years 8 months ago
Fitness importance for online evolution
To complement standard fitness functions, we propose "Fitness Importance" (FI) as a novel meta-heuristic for online learning systems. We define FI and show how it can be...
Philip Valencia, Raja Jurdak, Peter Lindsay
GECCO
2008
Springer
147views Optimization» more  GECCO 2008»
13 years 8 months ago
On selecting the best individual in noisy environments
In evolutionary algorithms, the typical post-processing phase involves selection of the best-of-run individual, which becomes the final outcome of the evolutionary run. Trivial f...
Wojciech Jaskowski, Wojciech Kotlowski
GECCO
2006
Springer
171views Optimization» more  GECCO 2006»
13 years 11 months ago
Evolving ensemble of classifiers in random subspace
Various methods for ensemble selection and classifier combination have been designed to optimize the results of ensembles of classifiers. Genetic algorithm (GA) which uses the div...
Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souz...
GECCO
2006
Springer
137views Optimization» more  GECCO 2006»
13 years 11 months ago
A method for parameter calibration and relevance estimation in evolutionary algorithms
We present and evaluate a method for estimating the relevance and calibrating the values of parameters of an evolutionary algorithm. The method provides an information theoretic m...
Volker Nannen, A. E. Eiben